Fifty nine percent of diabetic patients in the United States have lower extremity complications. Sensory impairment and functional abnormalities of localized capillary beds often result in foot ulcers that do not heal leading to infection, osteomyelitis and amputation. Methods of identifying individuals who are at risk of developing complications at the foot level include quantitative sensory testing, skin micro-circulation measurements and the assessment of macrovasculature patency. However, there are currently no practical non-invasive methods to determine the functional state of tissues that are located deep in the anatomy such as the muscles of the foot. A measurement of the metabolic activity in the muscles of the foot may provide an assessment of the functional ischemia brought about by microvascular abnormalities and help to identify patients who are at risk of developing diabetes-related complications,. While magnetic resonance spectroscopy (MRS) has been validated as a tool that can assess ischemia in muscle tissue by measuring the cellular phosphorus-31 (31P) metabolites, its use has been limited due to its poor spatial and temporal resolution. We have developed a 31P MRI method based on the rapid acquisition with relaxation enhancement (RARE) pulse sequence and applied it to normal subjects and diabetic patients on a 3 Tesla MRI scanner. We have acquired images with a spatial resolution of 0.47 cm x 0.47 cm x 2.5 cm in 4 minutes. Our results also indicate that the 31P signal intensities are uniform across the foot muscles of normal subjects while the signal values vary substantially across the foot muscles of diabetic patients. We have also successfully made accurate measurements of the concentrations of the 31P metabolites from 31P MR images and developed a chemically selective 31P MRI sequence. We now have the ability to acquire pure Pi and PCr images and create spatial maps of the Pi/PCr ratio. We have recently found that muscle atrophy and abnormal Pi/PCr ratios exist in diabetic patients before the detection of elevated clinical risk factors. We now propose to optimize the technique and extend its scope. We plan to correlate the Pi/PCr ratios calculated from 31P MR images to clinical risk factors in a diabetic population and measure the difference in the Pi/PCr ratio between diabetic patients with and without peripheral vascular occlusive disease (PAOD). We will also measure the change in metabolism by acquiring P and 1H MRI data of the feet of diabetic patients with PAOD before and after vascular bypass surgery and comparing the MRI results with clinical evaluations performed before and after surgery. The calibration and optimization proposed here will move this technique from a validated research project to a useful clinical tool for stratifying the risk of developing complications at the foot level by evaluating the metabolism of the foot muscles of diabetic patients with and without lower extremity complications.